Our Solutions
What we build, and one worked example in full.
Every engagement is architected for the problem in front of it. Below is the range we cover, followed by a working system described in detail rather than summarised.
Solution areas
Consultancy and delivery from the same team.
So advice and implementation do not drift apart.
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Business Consultancy
Operating model and process
Process discovery and mapping, bottleneck and cost analysis, target operating model, digital transformation roadmap, and business cases written for the people who approve budgets.
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AI Consultancy
Strategy, readiness and governance
AI readiness assessment, use-case discovery scored on value against effort, data-quality review, proof-of-concept design, team workshops, and governance covering privacy, accuracy and human oversight.
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IT Consultancy
Architecture, cloud and integration
Solution and enterprise architecture reviews, cloud migration and right-sizing, system integration and API strategy, resilience and disaster recovery, security posture and cost optimisation.
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Software Solutions
Custom applications and platforms
Web applications, portals and dashboards, data platforms and reporting, RESTful APIs and integrations, legacy modernisation, and accessible front-ends built to WCAG 2.1 AA.
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AI Software & Automation
Applied AI in production
Retrieval assistants grounded in your own documents, document and data extraction, classification and matching engines, recommendation systems, and workflow automation across existing tools.
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Support & Enablement
After go-live
Warranty and support windows, monitoring and incident response, documentation and runbooks, and handover training so your team can extend the system themselves.
Case study
STUDiPort Student Portal
A complete working system, shown here screen by screen rather than summarised in a paragraph.
- 50+programmes in one store
- 90,000+records, queryable
- 40:60UK classification rule, automated
- FHEQ 4–7CATS credits, ESCO skills, O*NET roles
The problem
Student academic records, degree classification, skills evidence and graduate opportunities lived in separate systems and spreadsheets. Students could not see where they stood; staff recalculated classifications by hand.
What we built
A single portal covering academic programmes and modules, grades with automated UK degree classification, a skills framework with evidence and instructor evaluation, a careers and job-matching portal, and role-based views for students, instructors and administrators.
Where the AI sits
Skills are mapped against standard taxonomies and matched to live job requirements, so a student sees the specific gap between their current profile and a target role, not a generic list of vacancies.
At a glance
| Sector | Higher education |
|---|---|
| Users | Students, instructors, administrators |
| Backend | Python 3.12, Flask, SQLAlchemy |
| Database | SQLite, PostgreSQL-ready via SQLAlchemy |
| Frontend | Jinja2 templates, CSS3 |
| API | RESTful JSON |
| Standards | UK CATS credits, FHEQ levels 4–7, ESCO skills, O*NET occupations |
| Accessibility | WCAG 2.1 AA, 4.5:1 contrast |
Student record
Modules, grades, evidence and instructor evaluation, in one place.
Skills mapped
Evidence is mapped to standard taxonomies: ESCO skills and O*NET occupations.
Matched to roles
Live job requirements are compared against the student’s current profile.
Gap shown
The student sees the specific gap to a target role, and what would close it.
Outcomes
- Classification calculated automatically under the 40:60 rule, including borderline promotion.
- 50+ programmes and 90,000+ records in one queryable store.
- Skills evidence and careers matching in the same place students already check grades.
The guided tour walks through twenty-four screens from the running application. For a live session against the system itself, ask us and we will arrange one.
Something similar on your side?
Send us the problem in a paragraph. We will tell you whether it needs architecture, software, automation, or none of the above.
Or email us directly: hello@globalsolark.co.uk